def main_process():
# get original path as str and list
path = os.getcwd()
list_path = path.split("/")
del list_path[0]
# get info from path
date = list_path[-3]
telescope = list_path[-5]
# get filters from path
temp = list_path[-1]
temp_list = temp.split("_")
filters = temp_list[0]
# go to the dir of calibrate
path_of_source = tat_datactrl.get_path("source")
path_of_calibrate = "{0}/{1}/calibrate".format(path_of_source, telescope)
os.chdir(path_of_calibrate)
# get a list of all object in calibrate
date_list = os.listdir(path_of_calibrate)
# find the nearest date reference to original date.w
result_date = match_date(date, date_list)
if result_date == -1:
print "date list has been zero, program ended"
return -1
# determind the exptime of flat
exptime = find_exptime(date, date_list, filters)
if exptime == -1:
print "date list has been zero"
return -1
# defind the dir of median flat, if it doesn't exist , create it.
path_of_median_flat = path_of_source + "/" + telescope + "/calibrate/" + result_date[
1] + "/median_flat_" + filters + "_" + exptime
print "path of median flat is :" + path_of_median_flat
if os.path.isdir(path_of_median_flat):
temp = "rm -r " + path_of_median_flat
os.system(temp)
temp = "mkdir -p " + path_of_median_flat
os.system(temp)
# get flat
os.chdir(result_date[1])
print os.getcwd()
number = get_flat_to(telescope, filters, result_date[1],
path_of_median_flat)
os.chdir("..")
if number < 10:
number = sub_process(telescope, filters, result_date,
path_of_median_flat, date, date_list)
if number < 10:
print "The number of flat is not enough, no median flat create."
return 0
os.chdir(path_of_median_flat)
temp = "finddark.py"
os.system(temp)
temp = "rm Median_flat*"
os.system(temp)
temp = "median_flat.py " + filters
os.system(temp)
temp = 'cp Median_flat*n.fits ' + path
os.system(temp)
os.chdir(path)
def main_process():
# get original path as str and list
path = os.getcwd()
list_path = path.split("/")
del list_path[0]
# get info from path
path_of_source = tat_datactrl.get_path("source")
temp_path = path.split(path_of_source)
temp_path_2 = temp_path[1].split("/")
date = temp_path_2[3]
telescope = temp_path_2[1]
# get exptime from path
temp = list_path[-1]
temp_list = temp.split("_")
exptime = temp_list[-1]
# go to the dir of calibrate
path_of_calibrate = path_of_source + "/" + telescope + "/calibrate"
os.chdir(path_of_calibrate)
# get a list of all object in calibrate
obj_list = os.listdir(path_of_calibrate)
# find the nearest date reference to original date.
result_date = match_date(date, obj_list)
# defind the dir of median dark, if it doesn't exist , create it
path_of_median_dark = path_of_source + "/" + telescope + "/calibrate/" + result_date[
1] + "/dark_" + exptime
print "path of median dark is :" + path_of_median_dark
if os.path.isdir(path_of_median_dark) == False:
temp = "mkdir -p " + path_of_median_dark
os.system(temp)
# get dark
os.chdir(result_date[1])
number = get_dark_to(telescope, exptime, result_date[1],
path_of_median_dark)
os.chdir("..")
# check whether the number of dark is enough, if no, find other darks.
if number >= 10:
os.chdir(path_of_median_dark)
temp = "median_fits dark"
os.system(temp)
Median_dark = "Median_dark_" + date + "_" + exptime + ".fits"
print "The dark name is :" + Median_dark
temp = "mv Median_dark.fits " + Median_dark
os.system(temp)
temp = "cp -R " + Median_dark + " " + path
os.system(temp)
else:
del obj_list[result_date[0]]
sub_process(path, telescope, obj_list, date, path_of_median_dark,
exptime)
os.chdir(path_of_median_dark)
temp = "median_fits dark"
os.system(temp)
Median_dark = "Median_dark_" + date + "_" + exptime + ".fits"
print "The dark name is :" + Median_dark
temp = "mv Median_dark.fits " + Median_dark
os.system(temp)
temp = "cp -R " + Median_dark + " " + path
os.system(temp)
list_name=argv[-1]
# read fits name from list
fits_list=tat_datactrl.readfile(list_name)
# get property of images from path
data_list = np.array([])
path = os.getcwd()
list_path = path.split("/")
scope_name = list_path[-5]
date_name = list_path[-3]
obj_name = list_path[-2]
filter_name = list_path[-1]
# write down header
path_of_result = tat_datactrl.get_path("result")
result_data_name = "{7}/limitation_magnitude_and_noise/{0}_{1}_{2}_{3}_{4}_{5}_{6}_N_to_t".format(obj_name, filter_name, date_name, scope_name, method, noise_unit, list_name, path_of_result)
result_fig_name = "{7}/limitation_magnitude_and_noise/{0}_{1}_{2}_{3}_{4}_{5}_{6}_N_to_t.png".format(obj_name, filter_name, date_name, scope_name, method, noise_unit, list_name, path_of_result)
result_file = open(result_data_name, "a")
result_file.write(obj_name + "_Noise_to_time\n")
result_file.write("filter: {0}\n".format(filter_name))
result_file.write("date: {0}\n".format(date_name))
result_file.write("scope: {0}\n".format(scope_name))
result_file.write("stack method: {0}\n".format(method))
result_file.write("list name: {0}\n".format(list_name))
# mention the noise has been normalize
result_file.write("normalize noise: yes")
if noise_unit == "count":
result_file.write("fitting function: noise = base/np.power(exptime, pow_) + const\n")
result_file.write("*************************************************************\n")
result_file.write("\t\t")
result_file.write("\n")
result_file.close()
#--------------------------------------------
# main code
VERBOSE = 0
# measure times
start_time = time.time()
# get property from argv
list_name = argv[-1]
fits_list = tat_datactrl.readfile(list_name)
# path of data source
path_of_source = tat_datactrl.get_path("result")
path_of_data_source = "{0}/TAT_row_star_catalog/".format(path_of_source)
os.chdir(path_of_data_source)
row_star_catalog_list = glob.glob("*.tsv")
# path of output
path_of_output = "{0}/TAT_star_catalog/".format(path_of_source)
os.chdir(path_of_output)
# list of band
for name in row_star_catalog_list:
if VERBOSE > 0: print "--- current: {0} ---".format(name)
# read a tsv file which haven't been prcoessed
name_list = name.split("_")
name_dir = "{0}{1}".format(path_of_data_source, name)
temp_data = tat_datactrl.read_tsv_file(name_dir)
date = name_list[1]
band = "{0}_{1}".format(name_list[3], name_list[4])